Simultaneous Image Classification and Restoration Using a Variational Approach

Herein, we present a variational model devoted to image classiication coupled with an edge-preserving regularization process. In the last decade, the varia-tional approach has proven its eeciency in the eld of edge-preserving restoration. In this paper, we add a classiication capability which contributes to provide images compound of homogeneous regions with regu-larized boundaries. The soundness of this model is based on the works developed on the phase transition theory in mechanics. The proposed algorithm is fast, easy to implement and eecient. We compare our results on both synthetic and satellite images with the ones obtained by a stochastic model using a Potts reg-ularization.